code: def testConcurrent(self):
      seed = [42, 24]
      matrix_shape = [3, 3]
      all_ops = []
      for adjoint_ in False, True:
          lhs1 = stateless_random_ops.stateless_random_normal(
              matrix_shape, seed=seed
          )
          lhs2 = stateless_random_ops.stateless_random_normal(
              matrix_shape, seed=seed
          )
          rhs1 = stateless_random_ops.stateless_random_normal(
              matrix_shape, seed=seed
          )
          rhs2 = stateless_random_ops.stateless_random_normal(
              matrix_shape, seed=seed
          )
          s1 = linalg_ops.matrix_solve(lhs1, rhs1, adjoint=adjoint_)
          s2 = linalg_ops.matrix_solve(lhs2, rhs2, adjoint=adjoint_)
          all_ops += [s1, s2]
      val = self.evaluate(all_ops)
      for i in range(0, len(all_ops), 2):
          self.assertAllEqual(val[i], val[i + 1])
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import benchmark
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling the MatrixSolveOpTest obj's underlying member method code with example usage: obj.testConcurrent() without return types